CAJ | 학술논문

文中研究了模糊多目标粒子群算法(MOPSO)在乙烯裂解工业中应用.算法在Pareto排序基础上引入子目标的最优操作条件来扩展属于非劣解集的操作条件范围,使非劣解集对于每个单目标而言都有较广的覆盖范围,确保非劣解集(操作条件)均匀分布,改进了非劣解集的质量,同时对非劣解引入工况实际要求,通过后验的模糊评价,来确定非劣解的满意操作条件,为决策者提供了明确的操作条件.将模糊多目标粒子群算法用于解决乙烯裂解过程中乙烯和丙烯收率多目标优化问题,较好地平衡了两种目标之间的冲突,为流程工业多目标优化问题提供了理论指导.
문중연구료모호다목표입자군산법(MOPSO)재을희렬해공업중응용.산법재Pareto배서기출상인입자목표적최우조작조건래확전속우비렬해집적조작조건범위,사비렬해집대우매개단목표이언도유교엄적복개범위,학보비렬해집(조작조건)균균분포,개진료비렬해집적질량,동시대비렬해인입공황실제요구,통과후험적모호평개,래학정비렬해적만의조작조건,위결책자제공료명학적조작조건.장모호다목표입자군산법용우해결을희렬해과정중을희화병희수솔다목표우화문제,교호지평형료량충목표지간적충돌,위류정공업다목표우화문제제공료이론지도.
In the paper, a fuzzy multi-objective Particle Swarm Optimization (MOPSO) hybrid algorithm applying to ethene cracking process was investigated. Pareto dominance and fuzzy decision.making were incorporated into panicle swarm optimization. Our algorithm took operation condition as repository of particles that was later used by other particles to guide their own flight. The optimum operation condition of every objective was incorperated into solution. Based on sort order, the scope and qulity of Pareto solution was extended. Satisfactory solution was get from Parcto set through fuzzy evaluate. The optimum operation condition was deduced.